{"id":"W1899685495","doi":"10.1111/j.1467-8667.2011.00732.x","title":"Hybrid Time‐Frequency Blind Source Separation Towards Ambient System Identification of Structures","year":2011,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":96,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Swedish Orphan Biovitrum","keywords":"Blind signal separation; Identification (biology); Computer science; Frequency domain; Energy (signal processing); Algorithm; Hilbert–Huang transform; Mathematics; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003233551,0.0005310412,0.0003863528,0.0004914463,0.0002284564,0.0005199237,0.0005348435,0.0006308498,0.001650988],"category_scores_gemma":[0.0009694278,0.0002119456,0.0004897313,0.0004706665,0.0003254188,0.0007999982,0.0007777757,0.0004964148,0.0007187027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001435697,"about_ca_system_score_gemma":0.000346996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005108171,"about_ca_topic_score_gemma":0.000721692,"domain_scores_codex":[0.999764,0.00006229047,0.000009867709,0.00004076003,0.0001027751,0.0000203434],"domain_scores_gemma":[0.9996873,0.0001416323,0.00003102426,0.00005139763,0.00007717693,0.00001149834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004863818,0.0001298664,0.0005383029,0.0002390428,0.0001236947,0.00008383216,0.000213718,0.1304127,0.3275641,0.01532264,0.001938249,0.5229475],"study_design_scores_gemma":[0.00003348537,0.00009076583,0.0007727135,0.00001242861,0.00003649377,0.0001359475,0.00002171117,0.924062,0.06480473,0.006463884,0.003543024,0.00002279996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009284762,0.00009022886,0.9899068,0.00002438731,0.00002044737,0.000005524948,0.00001154835,0.0001556123,0.0005005855],"genre_scores_gemma":[0.3913147,0.0005377024,0.5992965,0.00009649106,0.0001047331,0.0001239464,0.0001991351,0.0001317304,0.00819511],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001650988,"threshold_uncertainty_score":0.005523086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0100966014116902,"score_gpt":0.2220081456690892,"score_spread":0.211911544257399,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}